nicbet / sentiment-analysis-java

Domain-independent sentiment analysis via AFINN and SentiNet 3.0, written in Java

sentiment-analysis-java

Example implementation of AFINN and SentiNet 3.0 sentiment analysis.

Usage

• Build with gradle.
• Run the App main file with passing in a string to obtain AFINN and SentiNet3 scores.

Example

Calculate sentiment for a fictitious product review:

./gradlew run --args="'The product works really well. Does it exaclty what it says, well worth the price. Quality could be better.'"

> Task :run
AFINN SCORE: 4
SWN SCORE: 0.21629727936297283

BUILD SUCCESSFUL in 1s
2 actionable tasks: 1 executed, 1 up-to-date

AFINN

Implements AFINN-111.

AFINN is a list of English words rated for valence with an integer between minus five (negative) and plus five (positive). The words have been manually labeled by Finn Årup Nielsen in 2009-2011. The file is tab-separated. There are two versions:

AFINN-111: Newest version with 2477 words and phrases.

SentiNet 3.0

Sentiment scores are between -1 and 1, greater than 0 for positive and less than 0 for negative.

Dictionary-based sentiment analysis does not perform as well as a trained classifier, but it is domain-independent, based on a priori knowledge of words' sentiment values.

The class handles negations and multiword expressions.

Credits

AFINN: http://www2.imm.dtu.dk/pubdb/views/publication_details.php?id=6010 SentiNet 3.0: http://nmis.isti.cnr.it/sebastiani/Publications/LREC10.pdf